Breaking the (Benford) law: Statistical fraud detection in campaign finance

Research output: Contribution to journalArticlepeer-review


Benford's law is seeing increasing use as a diagnostic tool for isolating pockets of large datasets with irregularities that deserve closer inspection. Popular and academic accounts of campaign finance are rife with tales of corruption, but the complete dataset of transactions for federal campaigns is enormous. Performing a systematic sweep is extremely arduous; hence, these data are a natural candidate for initial screening by comparison to Benford's distributions.

Original languageEnglish (US)
Pages (from-to)218-223
Number of pages6
JournalAmerican Statistician
Issue number3
StatePublished - Aug 2007


  • Data irregularities
  • Data mining
  • FEC
  • First-digit distributions
  • Politics

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Statistics, Probability and Uncertainty


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